IRBM and flood protection?

Flooding scenario: Sweden

Flooding Facts: Vietnam Case

The average number of people killed per million inhabitants in disasters for the period 1980-2000 for Vietnam = 8.36

The average number of people killed per year =573 person/year

The numbers represented by floods for the same period are more the 25% of the total.

The Problem of FloodingFlood may be defined as the situation when the volume of water exceeds the capacity of a river channel, along a lake or coastal shorelines or in an urban area. The history of mankind has been accompanied by flooding since all the ancient civilizations in the world originated along the big rivers. Besides the natural phenomena causing floods (precipitation, snowmelt, cyclone, hurricane, typhoon etc), human activities in modern time have greatly intensified flooding problems from local scale to the global scale.

Cause of Floods

RainfallSnowmeltRunoffDam failureUrban storm runoffIce jamsCoastal stormsOthers (typhoon,

earthquake, etc)

Human Impact?

Climate Change vs. Human Impact:20th century

The average annual temperature rose by 0.8 °C in Europe.

Precipitation increased by 10-40 percent in northern Europe.

Southern Europe now have about 20 percent less rainfall.

Climate Change: Trends for the coming century

General Circulation Model (GCM) and high-resolution Regional Climate Models (RCM), it is concluded that these trend will continue for the coming century:

Temperature rising by between 0.1 and 0.4°C per decade

Raised frequency of natural catastrophes such as windstorms and floods.

Current Development and Modelling:Hydrology+3S (GIS, RS, GPS)

HydrologyPhysical Model

Numerical Model, DSS

RemoteSensing RS

Digital ImagingGPS, NN

GeographyMapping

GIS

1. Bishop, I.D., and C. Karadagli, (1996), Combining GIS based environmental modelling and visualization: another window in the modelling process.

2. Bell, M., Dean, C., and M. Blake, (2000), Forecasting the pattern of urban growth with PUP: a web-based model interfaced with GIS and 3D animation.

3. Beven, K.J., Warren, R., and Zaoui, J. (1980) SHE: towards a methodology for physically-based, distributed modelling in hydrology.

4. Bøhler, T., Karatzasb, K., and G. Peinelc, (2002), Providing multi-modal access to environmental Data-customizable information services for disseminating urban air quality information in APNEE.

5. DeVantier, B.A., and A.D. Feldman (1993), Review of GIS applications in hydrologic modelling.

6. Doyle, S., Dodge, M., & Smith, A. (1998), The potential of Web-based mapping and virtual reality technologies for modelling urban environments.

7. Djokic, D. and D.R. Maidment (1993), Application of GIS network routines for water flow and transport.

8. Fedra, K. and D.G. Jamieson (1996), An object-oriented approach to model integration: a river basin information system.

9. Flügel, W-A. (1996), Application of GIS to derive hydrological response units for hydrological modelling in the Bröl catchment, Germany.

10. Freeze, R.A., and Harlan, R.L. (1969) Blueprint for a physically-based, digitally-simulated hydrologic response model.

11. Kingston, R., Carver, S., Evans, A. and I. Turton (2000), Web-based public participation GIS.

12. Kuiper, J., Ayers, A., Johnson, R. and M. Tolbert-Smith (1996), Efficient data exchange: integrating a vector GIS with an object-oriented, 3-D visualization system.

13. Lam, D. and D. Swayne (1996), A hybrid expert system and neural network approach to environmental modelling: GIS applications in the RAISON system.

14. Leipnik, M.R., K.K. Kamp and H.A. Loaiciga (1993), Implementation of GIS for water resource planning and management.

15. Maidment, D.R. (1993), GIS and hydrological modelling. 16. Meyer, S.P., T.H. Salem, and J.W. Labadie (1993), Geographic

information systems in urban stormwater management. Muzik, I. (1992), Derivation of unit and flood hydrographs using a GIS.

Future Models1. An open architecture, inter-disciplinary

collaboration in methods development.2. Module based approach in database

management and model management, possible to incorporate new and other commercially available software

3. Data sharing between 3S (GIS, RS and GPS) and other models

4. Three-dimensional analyzing methodology and visualization

5. Object-oriented, multi-purpose approaches6. A user-friendly interface

Different Hydrological Models

Hydrological Simulation Models

Deterministic Stochastic

Empirical Lumped DistributedConceptual Physically-

Based

(Black box) (Gray box) (White box)

JointStochastic - Deterministic

Application in the field: River BasinsData Availability:

It is essential to have as clear as possible understanding of the mechanisms of flooding for an area for its disaster prevention and management. This understanding requires in turn great amount of data and field observations achieved by water resources assessment (WRA).

In reality the data collection and treatment are often mostly focused on geographical and spatial data such as base maps and GIS attributes (such as topography, coastlines, Land use, administrative boundaries, infrastructures, social-economical data, hydrography, geodesic network, DTM, contour lines, height spots, bathymetry etc).

Data Collection: Two categories

(A) Geographical and geophysical data of the watershed and river basin (such as drainage network, land/soil property, vegetation, hydraulic structure etc);

(B) Climatic and hydrological information and time series of historical records (precipitation, temperature, runoff/discharge, evaporation, wind, wave, sea level and groundwater level fluctuation etc).

Difficulties:

Category (A) data “spatial domain” and are relatively easy to collect and compile with combined 3S and satellite imagery .

Category (B) data historical field data based on long term observations from water resources assessment operations and they are in the “temporal domain”. This type of data are difficult to achieve afterwards if a well functioned field observation network was missing for the time periods.

Optimal Data Sets:

Social-economic

data

Hydraulic data

Geophysical watershed information

Meteorological and hydrological data

Types of Flood Simulation ModelsThere are many flood simulations models developed world wide. Depending on the characteristics of the problem and the purpose of the simulation, different types of models can be employed. According to the functions of these models, it can be categorized into:

Flood mapping modelsFlood forecasting modelsFlood warning modelsFlood design models

Flood Simulation ModelsngMod

ngMod

ngMod

ngMod

ngMod

ngMod

ng

Mod

ng

Mod

Mapping model + Forecasting model = Warning model ?

Conceptual schemeof a flood warning model

SHE Model:

The most comprehensive developments in a physically based model at the basin scale are the Systeme HydrologiqueEuropean (SHE), a collaborative research project of the Danish Hydraulic Institute (DHI), the Institute of Hydrology of Wallingford and Sogreah (Beven et al, 1980).

Conceptual structure of the MIKE-SHE model, DHI)

Other models we “used” recently

The Swedish model FLAPS (which was developed in cooperation with China)

The French model Bathysis (which was employed for flood mapping analysis)

The Dutch model STREAM reported by Bouwer(2002), Aerts, et al. (2002)

Model Country Main Functions

SWMM USA Storm Water Management Model. Runoff, transport, treatment of rainfall, routing, statistics. Mostly for urban areas.

HSPF USA The Hydrologic Simulation Program-Fortran (HSPF) has its origin in the Stanford Watershed Model developed by Crawford and Linsley (1966). Useful for large drainage basins.

DR3M USA Distributed Routing Rainfall-Runoff Model(DR3M). Rainfall treatment, runoff, routing

MIKE-SHE (DHI)Denmark

Flood Control Package. Can simulate all the major processes in the land phase of the hydrologic cycle and is applicable on spatial scales ranging from single soil profiles to regional watershed studies

MIKE FLOOD (DHI)Denmark

Dynamically linked 1-D and 2-D flood modelling package. Based on MIKE 11 and MIKE 21- and enhanced with new features which are targeted specifically towards modelling of floods. Coupling between river /floodplain or between the sea and inland waterways/bays/lagoons with GIS.

HEC-1 USA Flood Hydrograph Package. One of the industry-standard programs for hydrologic analysis. Nowadays included in Watershed Modelling System (WMS) - Graphical Interfaces to HEC-1, TR-20, NFF, Rational Method and HSPF.

PRMS USA Precipitation-Runoff Modelling System. useful for smaller watersheds to analyze impacts of land use.

TOPMODEL UK TOPMODEL (Beven and Kirkby 1979), Topography based rainfall-runoff model.

Case Study: La Paz - Bolivia• Southern districts

Example: Flood event in urban area

Example:

Heavily regulatedRiver-basinin Sweden

Reducing Flood vs.Reducing Impact of Flood

Flood Mitigation Measures

Structural (hardware) Non-structural (software) Physical Institutional

Flood mitigation measures and their interactions

Dams, reservoirs, and detention basins

Channel modifications

Levee banks

Flood forecasting, flood warning, andemergency planning

Schemes of drainage and floodprotection

Flood proofing

Catchment modifications

Planning controls

Flood insurance

Public information and education

Flood adaption

Acquisition and relocation

WATERCONTROL

MEASURES

LAND USECONTROL

MEASURES

STRUCTURALMEASURES

NONSTRUCTURAL

MEASURES FINANCIALRELIEF

AND LOSSREDUCTION

General RecommendationsEstablishment of an overall Water Resources Assessment (WRA) program:Long term field data collection, storage, compilation and analysis are fundamentals in understanding flooding problems. A DSS based hydrological modelling relies on this understanding.

Increased capacity building:Both human resource and institutional capacity building at national, regional and local levels need to be strengthened in order to ensure the effectiveness of flood mitigation measures.

Establishment of a knowledge database:Based on WRA and scientific analyses above, a knowledge database can be setup for easy access for all the authorities.

Establishment of flood generation mechanisms:Continuous scientific work should be carried out in analyzing flood generating mechanisms such as rainfall-runoff process, extreme weather-rainfall relation, wind-wave interaction, soil & groundwater fluctuations as well as catchment response to hydrological events.

Establishment of DSS based hydrological modelling system:Based on above mentioned points, a DSS based hydrological modelling becomes more meaningful and more accurate in providing flood scenarios and corresponding solutions.

General Recommendations

DSS and Hydrological Modeling

• Problems: Too many Models ?

Too difficult to use ?

Too little available data ?

Impossible for generalized use ?

Linus Zhang, TVRL/LU

The FLAPS Project background

Reservoir

Sub-basin

Inflow

Flood Detention

Outflow

Sketched map of structure of structural element in FLAPS

B a s in In i t ia l C o n d i t io n s

In p u t P a r a m e te r s

C r i te r ia* D a m d im e n s io n* R iv e r r e g u la t io n* D e t e n t io n b a s in* C o n s t r u c t io n s ta n d a r d* W a t e r s h e d d e s ig n & p la n n in g

D a ta P r e p r o c e s s

D e s ig nS c e n a r io s

R a in fa l l - r u n o f f M o d e l

R e s u lts & A n a ly s e s

D e c is io n M a k in g

B a s in D e f in i t io n & D e s ig n C r i te r ia (R a in fa l l o r R u n o f f )

F i tD e s ig n C r ite r ia ?

D a ta b a s e

Y e s

N o

Components of a DSS

Parameter DB

ApplicationProgram 1

Model DB

Result DB

GIS

Special DB

DBMS

ApplicationProgram i

ApplicationProgram n

……

Structure of DBMS and applications

Drainage network for Hongru river basin, China

Flood Diversion Node

D

D

R

D

RRR

N

N

N

N

N

NN

N N N

N

N

N

N

U U U

U

N

R

D

U

Collecting Node

Reservoir Node

Water User Node

River-Channel Line

Water Supply Line

Bantai

XincaiXuedian

Miaowan

Jiaotinghu

Wugouying

Guili

LaowangpoShakou

Panwan

Caifukou

Suyahu

Yangzhuang

ShimantanBanqiaoBoshan

Suiping

LEGEND

Laowangpo detension basin, Honngru river basin, China

General Evaluation: Selecting the optimal schemes Object Level

Politics Effect Society Effect Economy Effect Politics Effect Effect Level

For PoliticalStability & unity

For InternationalCommunication& Cooperation

For SocialEconomic

Development

For the Safety ofPeople’ s Life &

Property

For Construction&Emigration

For Developmentof Agriculture &

Industry

Economic Benefit& Cost Rate

Limited Years ofLoan Refund

Return Time ofInvestment

For Improvement& Beautificationof environment

For KeepingEcologicalBalance

N=10 N=50 N=100 N=1000

Index Level

Schemes Level

Structure of multi-factor and multi-level fuzzy evaluation

The interface of alternatives development in FLAPS

Weights Comparison of Evaluation in FLAPS

Evaluation result in FLAPS

The Final Goal

DSS for Smart Hydrological Modeling:

– Integrated model with GIS and RS

– Scalable and distributed in spatial and time domain

– Advanced DBMS for data analyses and manipulation

– Decision support based on modeling scenarios

– User friendly